From b051095d2638e5625f7778be7035d4d0390b310b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Sophia=20M=C3=A4dler?=
 <15019107+sophiamaedler@users.noreply.github.com>
Date: Sat, 30 Nov 2024 16:54:55 +0100
Subject: [PATCH] ruff linting

---
 src/scportrait/pipeline/featurization.py | 1 +
 src/scportrait/pipeline/project.py       | 5 +++--
 tests/e2e_tests/segmentation_workflow.py | 2 +-
 3 files changed, 5 insertions(+), 3 deletions(-)

diff --git a/src/scportrait/pipeline/featurization.py b/src/scportrait/pipeline/featurization.py
index 5363277c..12cadbfe 100644
--- a/src/scportrait/pipeline/featurization.py
+++ b/src/scportrait/pipeline/featurization.py
@@ -17,6 +17,7 @@
 from scportrait.tools.ml.datasets import HDF5SingleCellDataset
 from scportrait.tools.ml.plmodels import MultilabelSupervisedModel
 
+
 class _FeaturizationBase(ProcessingStep):
     PRETRAINED_MODEL_NAMES = [
         "autophagy_classifier",
diff --git a/src/scportrait/pipeline/project.py b/src/scportrait/pipeline/project.py
index 76e26c55..230842d9 100644
--- a/src/scportrait/pipeline/project.py
+++ b/src/scportrait/pipeline/project.py
@@ -4,6 +4,7 @@
 import tempfile
 import warnings
 from time import time
+from typing import Literal
 
 import dask.array as darray
 import datatree
@@ -33,7 +34,7 @@
     remap_region_annotation_table,
 )
 
-from typing import Literal
+
 class Project(Logable):
     CLEAN_LOG = True
 
@@ -1039,7 +1040,7 @@ def extract(self, partial=False, n_cells=None, overwrite: bool | None = None):
     def featurize(
         self,
         n_cells: int = 0,
-        data_type: Literal["complete", "partial", "filtered"] ="complete",
+        data_type: Literal["complete", "partial", "filtered"] = "complete",
         partial_seed: None | int = None,
         overwrite: bool | None = None,
     ):
diff --git a/tests/e2e_tests/segmentation_workflow.py b/tests/e2e_tests/segmentation_workflow.py
index fba12b6e..54d29157 100644
--- a/tests/e2e_tests/segmentation_workflow.py
+++ b/tests/e2e_tests/segmentation_workflow.py
@@ -6,8 +6,8 @@
 import pandas as pd
 
 from scportrait.pipeline._utils.segmentation import numba_mask_centroid
-from scportrait.pipeline.featurization import CellFeaturizer
 from scportrait.pipeline.extraction import HDF5CellExtraction
+from scportrait.pipeline.featurization import CellFeaturizer
 from scportrait.pipeline.project import Project
 from scportrait.pipeline.segmentation.workflows import CytosolSegmentationCellpose, ShardedCytosolSegmentationCellpose